This book explores the subject of artificial psychology and how the field must adapt human
neuro-psychological testing techniques to provide adequate cognitive testing of advanced
artificial intelligence systems. It shows how classical testing methods will reveal nothing
about the cognitive nature of the systems and whether they are learning reasoning and
evolving correctly for these systems the authors outline how testing techniques similar to
adapted from human psychological testing must be adopted particularly in understanding how the
system reacts to failure or relearning something it has learned incorrectly or inferred
incorrectly. The authors provide insights into future architectures capabilities that
artificial cognitive systems will possess and how we can evaluate how well they are
functioning. It discusses at length the notion of human AI communication and collaboration and
explores such topics as knowledge development knowledge modeling and ambiguity management
artificial cognition and self-evolution of learning artificial brain components and cognitive
architecture and artificial psychological modeling.Explores the concepts of Artificial
Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems
Provides insight into the world of cognitive architectures and biologically-based computing
designs which will mimic human brain functionality in artificial intelligent systems of the
future Provides description and design of artificial psychological modeling to provide insight
into how advanced artificial intelligent systems are learning and evolving Explores artificial
reasoning and inference architectures and the types of modeling and testing that will be
required to trust an autonomous artificial intelligent systems.
